Research ArticleOpen accessEvery word in the titleError Free Iterative Morphological Decomposition Algorithm for Shape RepresentationV. Vijaya Kumar, A. Srikrishna, G. Hemantha KumarProblem statement: A generalized skeleton transform allows a shape to be represented as a collection of modestly overlapped octagonal shape parts. One problem with several generalized Morphological skeleton transforms is that they generate noise after decomposition. The noise rate may not be effective for ordinary images; however this effect will be more when applied on printed or handwritten characters. Approach: … …Journal of Computer Science, Vol. 5, Issue 1 · 31 Jan 2009 · 7,517 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEmpirical Analysis and Mathematical Representation of the Path Length Complexity in Binary Decision DiagramsA. Assi, P. W.C. Prasad, B. Mills, A. ElchouemiInformation about the distribution of path-lengths in a Binary Decision Diagrams (BDDs) representing Boolean functions is useful in determining the speed of hardware and software implementations of the circuit represented by these Boolean functions. This study presents expressions produced from an empirical analysis of a representative collection of Boolean functions. The Average Path Length (APL) and the Shortest Path Length … …Journal of Computer Science, Vol. 2, Issue 3 · 31 Mar 2006 · 6,814 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleNeisser’s Cycle of Perception: Formal Representation and Practical ImplementationIgor A. Chimir, Waheeb A. Abu-Dawwas, Mark A. HorneyThis article presents results of a theoretical investigation of the application of the object-oriented Unified Modelling Language to a formal description of Neisser’s cycle of perception. The article includes class diagrams, modelling the spatial structure of Neisser’s cycle of perception and demonstrates how these formal descriptions can be applied to the area of modelling the problem-independent dialogue process. The basis … …Journal of Computer Science, Vol. 1, Issue 2 · 19 Oct 2005 · 5,104 accessesView PDFCite
Research ArticleOpen accessIn the keywordsConceptual Software Engineering Applied to Movie Scripts and StoriesSabah Al-FedaghiAccording to researchers, a large proportion of research software (software on which researchers rely) is fragile and the source of numerous problems that plague computational science. This study introduces another application of software engineering tools, conceptual modeling, which can be applied to other fields of research. One way to strengthen the relationship between software engineering and other fields is to … …Journal of Computer Science, Vol. 16, Issue 12 · 17 Dec 2020 · 7,132 accessesView PDFCite
Research ArticleOpen accessIn the keywordsUnderstanding the Code Transformation Algorithms' ImpactAnderson Faustino da Silva, Leonardo Deganello de SouzaModern compilers provide several code transformations, which are automatic program transformations applied with the goal of improving the program performance. In this article, we investigate how standard compiler code transformations, performed at the compiler intermediate representation, affect such representation and consequently the performance. Our research targets clang/LLVM, a popular compiler infrastructure. Our experimental evaluation demonstrates how several code transformations change … …Journal of Computer Science, Vol. 15, Issue 11 · 27 Nov 2019 · 7,347 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Convergence Theorem for Bivariate Exponential Dispersion ModelsLila Ricci, Gabriela BoggioMultivariate exponential dispersion models (MEDMs) were defined in 2013 by Jørgensen and Martínez. A particular case of MEDM is the bivariate Gamma model; in this article we prove that, under certain conditions, this is a limit distribution for MEDM generated by bivariate regularly varying measures, extending a previous result given by the aforementioned authors for the univariate case. As necessary … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 25 Jul 2019 · 6,582 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFake News Detection Using Weighted Fine-Tuned BERT and Sparse Recurrent Neural NetworkAsha Kathigi, Mukta Pujar, A M S Akshatha et al.Fake news refers to misinformation or false reports shared in the form of images, articles, or videos, disguised as real news to manipulate people’s opinions. Recently, fake news and rumors have spread extensively and rapidly around the world. This has led to the production and propagation of inaccurate news articles. Therefore, it is necessary to restrict the spread of fake … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,087 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMultiresolution Laplacian Sparse Coding Technique for Image ClassificationIntidhar Jemel, Ridha Ejbali, Mourad ZaiedSparse coding is a set of techniques used for learning a collection of over-complete bases to represent data efficiently. This technique has been used in different domain such as feature quantization and image classification. Despite its capacity of modeling, it could not represent similarity of the image coding which cause a poor performance in locality. The cause of this limitation … …Journal of Computer Science, Vol. 14, Issue 8 · 23 May 2018 · 7,920 accessesView PDFCite
Research ArticleOpen accessIn the keywordsLow-Homology Protein Structural Class Prediction from Secondary Structure Based on Visibility and Horizontal Visibility NetworkZhi-Qin Zhao, Liang Luo, Xiao-Yan LiuIn this study, based on the predicted secondary structures of proteins, we propose a new approach to predict protein structural classes (α,β,α/β,α+β) for three widely used low-homology data sets. Fist, we obtain two time siries from the chaos game representation of each predicted secondary structure; second, based on two time series, we construct visibility and horizontal visibility network, respectively and … …American Journal of Biochemistry and Biotechnology, Vol. 14, Issue 1 · 12 Mar 2018 · 9,668 accessesView PDFCite
Research ArticleOpen accessIn the keywordsObject Recognition Based on Image Segmentation and ClusteringS. Thilagamani, N. ShanthiProblem statement: This study deals with object recognition based on image segmentation and clustering. Acquiring prior information of an image is done via two separate processes. Approach: The first process deals with detecting object parts of an image and integration of detected parts into several clusters. All these cluster centers form the visual words. The second process deals with over … …Journal of Computer Science, Vol. 7, Issue 11 · 6 Sep 2011 · 7,074 accessesView PDFCite